Probability estimation in poker: A qualified success for unaided judgment

James Liley, Tim Rakow*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


Poker players make strategic decisions on the basis of imperfect information, which are informed by their assessment of the probability they will hold the best set of cards among all players at the conclusion of the hand. Exact mental calculations of this probability are impossible-therefore, players must use judgment to estimate their chances. In three studies, 69 moderately experienced poker players estimated the probability of obtaining the best cards among all players, based on the limited information that is known in the early stages of a hand. Although several of the conditions typically associated with well-calibrated judgment did not apply, players' judgments were generally accurate. The correlation between judged and true probabilities was r > 8 for over five-sixths of the participants, and when judgments were averaged across players and within hands this correlation was 96. Players slightly overestimated their chance of obtaining the best cards, mainly where this probability was low to moderate (<.7). Probability estimates were slightly too strongly related to the strength of the two cards that a player holds (known only to themselves), and insufficiently influenced by the number of opponents. Seemingly, players show somewhat insufficient regard for the cards that other players could be holding and the potential for opponents to acquire a strong hand. The results show that even when judgment heuristics are used to good effect in a complex probability estimation task, predictable errors can still be observed at the margins of performance.
Original languageEnglish
Pages (from-to)496-526
Number of pages31
JournalJournal of Behavioral Decision Making
Issue number5
Publication statusPublished - Dec 2010


  • Anchoring and adjustment
  • Anchors
  • Calibration
  • Expertise
  • Heuristics
  • Probability judgment
  • Simulation heuristic
  • Support theory


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